As is well known in the prior art, a video image, when digitized, requires a large amount of storage. A plurality of video images (as used hereinafter: "a video scene"), such as a movie, would require hundreds of megabytes or even gigabytes of storage, if not compressed.
Methods to compress a video scene are also well known in the prior art. One prior art method is to derive a parameter by principal component analysis for all the images of the video scene. Let us assume that each video image has N pixels. Thereafter, an image value based upon the parameter chosen by principal component analysis is determined for each of the video images. Thus, the resultant storage requirement, for one parameter, would be one image full of component values for that parameter (or N values) and one image value associated with each video image. If more than one parameter is derived for the video images, the total amount of storage required would be multiplied correspondingly.
However, even with this method, if the video scene has many video images, such as a movie, the storage required for a single value of the parameter associated with each of the video images would still be large. Since video images are displayed at a rather rapid rate, e.g., thirty times per second, a two hour video movie would require 216,000 video images (2.times.60.times.60.times.30) and at standard TV format would require 50 gigabyte of storage. Therefore, based on this method, for one parameter, there would still require N number of parameter component values, derived by principal component analysis, and 216,000 image values with one image value for each of the video images.
Furthermore, although storage requirement is reduced by this method, compared to the uncompressed video scene, to review or browse through the video images of this video scene would require the display of the entire collection of images, e.g. 216,000 images. To a user, viewing or searching through the entire collection of displayed images would be inefficient and cumbersome. Browsing or skimming through the entire collection of video images of the video scene would require a considerable mount of time and effort.
Another method of compression of the prior art is to choose some of the images from a video scene as reference frames. Subsequent or preceding images are compared to the reference frames, and the differences or changes are stored. Thus, data for only the reference frames and the changes thereto need to be stored.
However, in such prior art method, the reference frames are chosen based upon every nth frame. Thus, the choice of the reference frame is not optimized.
As the use of video images to capture information becomes more prevalent, a method must be found to efficiently store, display and search the plurality of video images, or the video scene. The collection of video images displayed must be categorized in a manner permitting rapid searching. Thus, not only is the compression of the video images important to minimize storage space, but the method must further facilitate the display and rapid searching of the compressed video images.
Hence, the present invention deals with the problems of video compression to minimize storage requirement as well as to permit a more efficient method of displaying and searching video images from a video scene.